Readings on EES 4760/5760

The computer modeling cycle

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 1.
Handout: P. Tyson, “Artificial Societies,” Technology Review 100 (3), 15–17 (1997)..

Optional Extra Reading:

Modeling Social Behavior, Ch. 1.

Reading Notes:

This reading sets the stage for answering the questions:

What is computational modeling and why is it useful in social and natural science research?
What are agent based models? How are they different from other kinds of models? What makes them useful for scientific research?

The reading introduces the idea of a modeling cycle. You should understand the different steps in the modeling cycle. You should also think about why Railsback and Grimm describe modeling as a cycle, as opposed to a linear process with a start and stop.

Introduction to NetLogo

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 2.

Optional Extra Reading:

Modeling Social Behavior, Ch. 2.

Reading Notes:

Familiarize yourself with NetLogo. I recommend that you read through the chapter with NetLogo open on your computer. Feel free to play around with NetLogo and try things out. The homework consists of following the step-by-step creation of a model in section 2.3.

The chapter from Modeling Social Behavior is purely optional. You don’t need to read it, and everything you need to know is covered in the reading from Railsback & Grimm, but it may be interesting to read this alternate introduction to the NetLogo modeling system and programming language.

Specifying models: The ODD protocol

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 3.

Reading Notes:

Read carefully through the different design principles. Some of them have meanings that are a bit different from what you might infer from colloquial use.

For instance:

Adaptation does not mean a persistent change in a turtle’s behavior similar to the biological/Darwinian sense of adaptation in species. Rather, it means the way an agent changes its behavior in response to its immediate conditions. Thus, adaptation in the ODD sense might include behaviors such as eating when you are hungry (eating is an adaptation to hunger), putting on warmer clothing when it’s cold out (bundling up is an adaptation to cold), and running away from a predator.
The kind of persistent changes that arise over time from experience fall under the ODD design concept of learning: If there is more food near a river than on hills, turtles may learn to go to rivers when they are hungry.

You can download several useful documents related to the ODD protocol from the class web site:

Your first model

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 4.

Reading Notes:

For the reading, read Chapter 4 in Agent-Based Modeling first and focus mostly on this chapter.

It is worth noting that the Sugarscape model you read about for Aug. 25 is very similar to the hilltopping model. Sugarscape was part of a very influential research project in the 1990s, in which Joshua Epstein and Robert Axtell showed that a very simple model could reproduce complex biological and economic phenomena that are observed in real societies and ecosystems. You may find it interesting at this point to look back at the “Artificial Societies” article and to play with the Sugarscape model in NetLogo.

Using models for science

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 5.

Optional Extra Reading:

Modeling Social Behavior, Ch. 3.

Reading Notes:

This reading sets the stage for answering the big question, “How can we use agent-based models to do science?” There are several aspects to this question, which this chapter will introduce:

How can we produce quantitative output from our models?
How can your models read and write data to and from files? (This is important for connecting your model to other parts of your project)
How should we test our models to make sure they do what we think they do? (More on this in Chapter 6)
Making your research reproducible by using version control and documentation.

A number of you may like to use Excel or statistical analysis tools, such as R, SPSS, or Stata. The material in this chapter about importing and exporting data using text or .csv files will be very useful for this. By default, NetLogo only allows you to read in data in simple text files. However, if comes with some extensions that you can use to read in data from other common file formats, including .csv and ArcGIS shapefiles and raster (grid) files.

Testing and validating models

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 6.

Reading Notes:

No one writes perfect programs. Errors in programs controlling medical equipment have killed people. Errors in computer models and data analysis code have not had such dire results, but have wasted lots of time for researchers and have caused public policy to proceed on incorrect assumptions. In many cases, these errors were uncovered only after a great deal of frustration because the original researchers would not share their computer codes with others who were suspicious of their results.

Choosing Research Projects

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 7.

Reading Notes:

There is not very much reading for today. Read Chapter 7 of Agent-Based Modeling carefully (it’s very short) The point of this chapter is to help you get ideas for your term research project.

Before class, I want you to read through the research project assignment and think about what you might want to do for a research project. We will spend class talking about possible research projects.

Emergence

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 8.

Reading Notes:

This is a major chapter. Emergence is one of the most important concepts in agent-based modeling, so pay close attention to the discussion in this chapter and think about how you can measure and assess emergence.

This chapter also introduces a very important tool for doing experiments in NetLogo: BehaviorSpace. BehaviorSpace lets you repeatedly run a NetLogo model while varying the settings of any of the controls on your user interface. Where there is randomness (stochasticity) in the model, you can perform many runs at each set of control settings. This will let us perform sensitivity analysis to determine whether a certain emergent phenomenon we are investigating happens only for values of the parameters within a narrow range, or whether it happens over a wide range of the parameters. It will let us determine which parameters are most important for the phenomenon.

Observation

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 9.

Reading Notes:

In this chapter, we examine how to detect and record the properties of a model that we want to study.

The article, D. Kornhauser, U. Wilensky, and W. Rand. (2009). “Design guidelines for agent-based model visualization,” Journal of Artificial Societies and Social Simulation 12, 1 is available online at https://jasss.soc.surrey.ac.uk/12/2/1.html.

I have posted a refresher guide for NetLogo programming on the class web site at https://ees4760.jmgilligan.org/files/models/chapter_09/ch9_ex8_netlogo_exercises.pdf

Sensing

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 10.

Reading Notes:

In addition to the assigned reading from the textbook, read the ODD for your team project before you come to class. The ODDs are posted on Brightspace and the class web site.

For some of the class period, you and your team will start translating the ODD for your project model into NetLogo code.

Important programming concepts in this chapter include:

Adaptive Behavior and Objectives

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 11.

Reading Notes:

Agents’ behavior often consists of trying to achieve some objective.

I have discussed the way that Adam Smith’s “invisible hand of the market” is a kind of agent-based view of a nation’s economy: Each person (agent) has an objective of trying to maximize his or her own wealth (that’s the agent’s micromotive), and in doing so, the population of agents manages unintentionally to maximize the total wealth of the nation (an emergent macrobehavior that results from the collective interactions of the agents and their micromotives).

Prediction

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 12.

Reading Notes:

In class, we will discuss the telemarketer model.

For the teams working on the telemarketer model, the steps are:

Build the model as described in the ODD.
Do the analyses in section 13.3.2
Next work on two extensions:
1. Mergers (section 13.5)
2. Customers remember (section 13.6)

Before class, everyone should read Chapter 13 and the ODD for the telemarketer model and be ready to discuss the model in class. This will be a chance for the teams working on the model to ask questions.

Interaction

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 13.

Optional Extra Reading:

Modeling Social Behavior, Ch. 6–7, 9.

Reading Notes:

The optional reading from Modeling Social Behavior may be interesting. Chapters 6–7 apply agent-based modeling to game-theory and chapter 9 looks into social networks among agents in detail.

Chapter 6 focuses on a class of strategic games, such as the Prisoner’s Dilemma, in which the players do better when they cooperate with each other, but the game gives each player has a strong temptation to betray their partner. The chapter investigates a rich line of research, which shows that there may be reasons for natural selection to favor cooperation, so people may have evolved to be mostly trustworthy and cooperative.

Team Presentations

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

No new reading for today.

Notes:

There is no reading for today. You will do your team project presentations in class.

Research Project ODDs

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

No new reading for today.

Notes:

There is no reading for today. We will spend class discussing your individual projects and your work on creating an ODD for your model.

Scheduling

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 14.

Reading Notes:

A good example of asynchronous updating is the model of breeding synchrony, described in Jovani and Grimm (2008) and in Chapter 23, which I have posted on the class web site: https://ees4760.jmgilligan.org/files/models/chapter_23/Ch_23_4_breeding_synchrony.nlogo

Stochasticity

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 15.

Collectives

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 16.

Patterns

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 17–18.

Reading Notes:

You can download the ODD for the BEFORE beech forest model, which is described in section 18.3, from the class web site: https://ees4760.jmgilligan.org/files/models/chapter_18/ch18_before_ODD.pdf.

I have also posted a list of published models in which observed patterns are important: https://ees4760.jmgilligan.org/files/models/chapter_18/ch18_ex1_models_list.pdf

Theory Development

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 19.

Optional Extra Reading:

Modeling Social Behavior, Ch. 8.

Reading Notes:

There is an implementation of the wood hoopoe model, suitable for Exercise 2, on the class web site: https://ees4760.jmgilligan.org/files/models/chapter_19/ch19_ex2_wood_hoopoes.nlogo

The optional chapter from Modeling Social Behavior discusses other approaches to using agent-based models to do science. The readings from Railsback & Grimm focus on the methodology of Pattern-Oriented Modeling. This chapter looks at other ways of thinking about connecting agent-basedm models to scientific methods. The focus here is on statistical analysis of experimental results and the use of Bayesian statistical methods to identify and avoid pitfalls where experiemnts may fool researchers into drawing the wrong conclusion (e.g., thinking a hypothesis is true, when it’s really false).

Parameterization and Calibration

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 20.

Agent-Based Models in Practice

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

No new reading for today.

Analyzing ABMs

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 22.

Sensitivity and Robustness

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 23.

Reading Notes:

You can download the model of breeding synchrony, described in Jovani and Grimm (2008) and in section 23.4, from the class web site: https://ees4760.jmgilligan.org/files/models/chapter_23/Ch_23_4_breeding_synchrony.nlogo

Looking Ahead: ABMs Beyond this Course

Thu, 31 Jul 2025 00:00:00 +0000

Reading:

Required Reading (everyone):

Agent-Based and Individual-Based Modeling, Ch. 24.

Optional Extra Reading:

Modeling Social Behavior, Ch. 10–11.

Reading Notes:

The optional reading from Modeling Social Behavior provides perspectives on the relationship between simulation models and the real world and how to use models wisely by appreciating both what they can do and what they can’t do, what parts of the real world they capture faithfully and which parts they don’t.